Roberto De Prisco

2.3k citations
82 papers · 1.1k · h-index 19

Impact in

Papers in

Roberto De Prisco

76 papers receiving 1.0k citations

Peers

Roberto De Prisco
Comparison fields: 5 of 76
  • Computer Vision and Pattern Recognition 512
  • Computer Networks and Communications 350
  • Signal Processing 151
  • Artificial Intelligence 334
  • Music 29
Replace Jean-Pierre Briot with:
Jean-Pierre Briot France
T. Raita Finland
Domagoj Vrgoč Chile
Stavros Christodoulakis Greece
Juan L. Reutter Chile
Alex Thomo Canada
Teng-Sheng Moh United States
E. Koutsofios United States
Claus Lewerentz Germany
Daniel S. Hirschberg United States
Roberto De Prisco relative to Jean-Pierre Briot France Jean-Pierre Briot's profile →
Citations per field
00.5×7.6×
Jean-Pierre Briot · 1×
Citations per year

Countries citing papers authored by Roberto De Prisco

Since Specialization
Citations

This map shows the geographic impact of Roberto De Prisco's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Roberto De Prisco with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Roberto De Prisco more than expected).

Fields of papers citing papers by Roberto De Prisco

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Roberto De Prisco. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Roberto De Prisco. The network helps show where Roberto De Prisco may publish in the future.

Co-authors

The 25 scholars most cited alongside Roberto De Prisco, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Roberto De Prisco Line = papers co-authored together Roberto De Prisco links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 82 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2005149
2 200077
3 200557
4 201457
5 200447
6 200745
7 200440
8 200537
9 199434
10 201931
11 200126
12 201025
13 201623
14 201322
15 202122
16 201321
17 201920
18 199820
19 201618
20 200817

About Roberto De Prisco

Roberto De Prisco is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Computer Networks and Communications, Signal Processing and Computational Theory and Mathematics, having authored 82 papers that have together received 1.1k indexed citations. Recurring topics across this work include Music Technology and Sound Studies (14 papers), Music and Audio Processing (13 papers), Chaos-based Image/Signal Encryption (11 papers), Advanced Steganography and Watermarking Techniques (10 papers), Cryptography and Data Security (9 papers), Distributed systems and fault tolerance (9 papers), Algorithms and Data Compression (8 papers) and DNA and Biological Computing (6 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (512 citations), Computer Networks and Communications (350 citations), Signal Processing (151 citations), Artificial Intelligence (334 citations) and Music (29 citations). Roberto De Prisco has collaborated with scholars based in Italy, United States and Spain. Frequent co-authors include Alfredo De Santis, Stelvio Cimato, Rocco Zaccagnino, Nancy Lynch, Delfina Malandrino, Butler Lampson, Juan A. Garay, Moti Yung, Bruce M. Maggs and Nicola Lettieri. Their work appears in journals such as Theoretical Computer Science, The Computer Journal, IEEE Transactions on Information Theory, Designs Codes and Cryptography and IEEE Transactions on Dependable and Secure Computing.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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